Title

A Novel Human-Computer Collaboration: Combining Novelty Search With Interactive Evolution

Keywords

Deception; Evolutionary computation; Fitness; Human-led search; Interactive evolutionary computation; Non-objective search; Novelty search; Serendipitous discovery; Stepping stones

Abstract

Recent work on novelty and behavioral diversity in evolutionary computation has highlighted the potential disadvantage of driving search purely through objective means. This paper suggests that leveraging human insight during search can complement such novelty- driven approaches. In particular, a new approach called noveltyassisted interactive evolutionary computation (NA-IEC) combines human intuition with novelty search to facilitate the serendipitous discovery of agent behaviors in a deceptive maze. In this approach, the human user directs evolution by selecting what is interesting from the on-screen population of behaviors. However, unlike in typical IEC, the user can now request that the next generation be filled with novel descendants. The experimental results demonstrate that combining human insight with novelty search not only finds solutions significantly faster and at lower genomic complexities than fully-automated processes guided purely by fitness or novelty, but it also finds solutions faster than the traditional IEC approach. Such results add to the evidence that combining human users and automated processes creates a synergistic effect in the search for solutions. © 2014 is held by the owner/author(s).

Publication Date

1-1-2014

Publication Title

GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference

Number of Pages

233-240

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1145/2576768.2598353

Socpus ID

84905702252 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84905702252

This document is currently not available here.

Share

COinS